OptimizelyConfig
This topic describes how to get access to project configuration data within the datafile using OptimizelyConfig.
Overview
Full Stack SDKs open a well-defined set of public APIs, hiding all implementation details. However, some clients may need access to project configuration data within the datafile.
In this document, we extend our public APIs to define data models and access methods, which clients can use to access project configuration data.
OptimizelyConfig API
A public configuration data model (OptimizelyConfig) is defined below as a structured format of static Optimizely Project data.
Get OptimizelyConfig
OptimizelyConfig can be accessed from OptimizelyClient (top-level) with this public API call:
def get_optimizely_config(self)
getOptimizelyConfig
returns an OptimizelyConfig
instance which includes
- environment key
- SDK key
- the datafile revision number
- all experiments mapped by their key values
- all attributes
- all audiences
- all events
- feature flags mapped by their key values
- function to retrieve the project configuration (the datafile)
Note
When the SDK datafile is updated (the client can add a notification listener for
OPTIMIZELY_CONFIG_UPDATE
to get notified), the client is expected to call the method to get the updated OptimizelyConfig data. See examples below.
Get datafile
To share the same datafile between multiple SDK instances (for example, in a client/server scenario), you can pass a JSON string representation of the config (the datafile) between the instances. To get the datafile, use the OptimizelyConfig
object's getDatafile
method. For more information, see Sharing the datafile with multiple SDK implementations.
Object model
The following shows the object model for OptimizelyConfig.
class OptimizelyConfig(object):
def __init__(self, revision, experiments_map, features_map, sdk_key=None, environment_key=None, attributes=None, events=None,
audiences=None):
self.revision = revision
# This experiments_map is for experiments of legacy projects only.
# For flag projects, experiment keys are not guaranteed to be unique
# across multiple flags, so this map may not include all experiments
# when keys conflict.
self.experiments_map = experiments_map
self.features_map = features_map
self.sdk_key = sdk_key or ''
self.environment_key = environment_key or ''
self.attributes = attributes or []
self.events = events or []
self.audiences = audiences or []
class OptimizelyExperiment(object):
def __init__(self, id, key, variations_map, audiences=''):
self.id = id
self.key = key
self.variations_map = variations_map
self.audiences = audiences
class OptimizelyFeature(object):
self.id = id
self.key = key
self.variables_map = variables_map
self.delivery_rules = []
self.experiment_rules = []
# Deprecated. Use experiment_rules and delivery_rules.
self.experiments_map = experiments_map
class OptimizelyVariation(object):
def __init__(self, id, key, feature_enabled, variables_map):
self.id = id
self.key = key
self.feature_enabled = feature_enabled
self.variables_map = variables_map
class OptimizelyVariable(object):
def __init__(self, id, key, variable_type, value):
self.id = id
self.key = key
self.type = variable_type
self.value = value
class OptimizelyAttribute(object):
def __init__(self, id, key):
self.id = id
self.key = key
class OptimizelyEvent(object):
def __init__(self, id, key, experiment_ids):
self.id = id
self.key = key
self.experiment_ids = experiment_ids
class OptimizelyAudience(object):
def __init__(self, id, name, conditions):
self.id = id
self.name = name
self.conditions = conditions
Examples
OptimizelyConfig can be accessed from OptimizelyClient (top-level) like this:
config = optimizely_client.get_optimizely_config()
print('REVISION ', config.revision)
print('SDK KEY ', config.sdk_key)
print('ENV KEY ', config.environment_key)
print("[OptimizelyConfig] revision = ", config.revision)
print("[OptimizelyConfig] sdk_key = ", config.sdk_key)
print("[OptimizelyConfig] environment_key = ", config.environment_key)
print("[OptimizelyConfig] attributes:")
for attribute in config.attributes:
print('[optimizelyConfig] - (id, key) ', attribute.id, attribute.key)
print("[OptimizelyConfig] audiences:")
for audience in config.audiences:
print('[OptimizelyConfig] - (id, name, conditions) ', audience.id, audience.name, audience.conditions)
print("[OptimizelyConfig] events:")
for event in config.events:
print("[OptimizelyConfig] - (id, key, experimentIds) ", event.id, event.key, event.experiment_ids)
# all flags
flags = config.features_map.values()
print('[OptimizelyConfig] - flags ', flags)
flag_keys = config.features_map.keys() # swift
print('[OptimizelyConfig] - flag keys ', flag_keys)
for flag_key in flag_keys:
flag = config.features_map[flag_key]
experiment_rules = flag.experiment_rules
delivery_rules = flag.delivery_rules
print(experiment_rules)
print(delivery_rules)
# use experiment rules and delivery rules and other flag data here...
for experiment in experiment_rules:
print("[OptimizelyConfig] - experiment rule-key = ", experiment.key)
print("[OptimizelyConfig] - experiment audiences = ", experiment.audiences)
print("[OptimizelyConfig] - experiment variations map = ", experiment.variations_map)
variations_map = experiment.variations_map
variation_keys = variations_map.keys()
for variation_key in variation_keys:
print("[OptimizelyConfig] - variation = ", variation_key) # not the same as in swift!
map_of_variables = variations_map[variation_key].variables_map
variable_keys = map_of_variables.keys()
for variable_key in variable_keys:
variable = map_of_variables[variable_key]
print('[OptimizelyConfig] - variable = ', variable_key, variable.value)
for delivery in delivery_rules:
print("[OptimizelyConfig] - delivery rule-key = ", delivery.key)
print("[OptimizelyConfig] - delivery audiences = ", delivery.audiences)
# listen to OPTIMIZELY_CONFIG_UPDATE to get updated data
def on_config_update_listener(*args):
config = optimizely_client.get_optimizely_config()
optimizely_client.notification_center.add_notification_listener(
enums.NotificationTypes.OPTIMIZELY_CONFIG_UPDATE, on_config_update_listener)
Updated over 2 years ago